white acrylic or other white background (contruction paper, white painted cardboard, bench paper)
plant of choice
find a flat surface with access to power. Place ring stand on surface and tighten clasp at preferred height. place white background below the viewing area of the camera
attach raspberrypi camera to raspberrypi microcomputer using the ribbon cable
attach raspberrypi camera to ring clasp
secure raspberrypi microcomputer to ring clasp (ex. zip ties)
plug in hdmi cable, USB-C power cable, 256GB thumb drive, and
mouse/keyboard to microcomputer HDMI/USB-C/USB ports, respectively
plug in cables to monitor (HDMI, keyboard, mouse) or power source (USB-C power cable)
once you are connected to the monitor, test your camera using the command libcamera-hello in terminal
place your focal species in erlenmeyer flask below the camera
use the command libcamera-vid in terminal
adjust your camera settings (focus and aperature) using the two knobs on the raspberry pi camera
(optional) if you do not have a consisten light source (ex. motion sensor lights), attach a utility light to your ring stand and aim the light at your target, adjust aperature accordingly
cut off individual leaves and place on the leafbyte scale
adjust height of raspberrypi module (microcomputer + camera) and camera settings accordingly
use the command libcamera-jpeg -o /folderpath/filename.jpeg to take a picture of your damaged leaf
save the bash script: record_video.sh to your raspberrypi (see github link above)
open crontab by running the command: crontab -e in terminal
use the nano-1 crontab, and adjust crontab to take videos on schedule and run the record_video.sh script (see github links above)
reboot your pi to engage the new crontab
check the folder you have set the videos to be saved in to make sure videos are being recorded
download leafbyte from link in setup
follow instructions from leafbyte to save herbivory data
download python file (import cv2.py) from github (see link above)
run in terminal:
use command cd to enter directory containing the python file, ex. cd /path_to_file/
enter python3 import_cv2.py
or run in preferred GUI (ex. VSCode)
remember to change pathnames!
note that you may choose to use a different method for blob tracking, this is very basic
*** Please note that links are just suggestions, and may no longer be available or ideal for your needs, please use your best judgment to purchase items that are appropriate for your project